SAMSUNG ELECTRONICS CO., LTD. 750XGK
Geekbench AI Score
1669
Single Precision Score
1667
Half Precision Score
3853
Quantized Score
Geekbench AI 1.4.0 for Windows AVX2
Result Information
| User | harsidh |
| Upload Date | July 08 2025 12:55 PM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | 13th Gen Intel(R) Core(TM) i3-1315U |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home Single Language (64-bit) |
| Model | SAMSUNG ELECTRONICS CO., LTD. 750XGK |
| Motherboard | SAMSUNG ELECTRONICS CO., LTD. NP750XGJ-LG4IN |
| Power Plan | Samsung Mode |
| CPU Information | |
|---|---|
| Name | Intel Core i3-1315U |
| Topology | 1 Processor, 6 Cores, 8 Threads |
| Identifier | GenuineIntel Family 6 Model 186 Stepping 3 |
| Base Frequency | 1.20 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 8.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
795
147.9 IPS |
|
|
Image Classification (HP)
|
100% |
806
149.9 IPS |
|
|
Image Classification (Q)
|
100% |
2399
446.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
1293
21.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
1297
21.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
2227
36.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
2260
2.64 IPS |
|
|
Pose Estimation (HP)
|
100% |
2251
2.63 IPS |
|
|
Pose Estimation (Q)
|
96% |
6473
7.58 IPS |
|
|
Object Detection (SP)
|
100% |
907
72.0 IPS |
|
|
Object Detection (HP)
|
100% |
849
67.3 IPS |
|
|
Object Detection (Q)
|
88% |
2468
197.9 IPS |
|
|
Face Detection (SP)
|
100% |
2499
29.7 IPS |
|
|
Face Detection (HP)
|
100% |
2457
29.2 IPS |
|
|
Face Detection (Q)
|
100% |
5382
64.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
2568
19.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
2587
19.9 IPS |
|
|
Depth Estimation (Q)
|
89% |
6201
48.2 IPS |
|
|
Style Transfer (SP)
|
100% |
6639
8.53 IPS |
|
|
Style Transfer (HP)
|
100% |
6701
8.61 IPS |
|
|
Style Transfer (Q)
|
98% |
17638
22.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1207
44.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1216
44.9 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
3681
136.3 IPS |
|
|
Text Classification (SP)
|
100% |
1000
1.33 KIPS |
|
|
Text Classification (HP)
|
100% |
1034
1.38 KIPS |
|
|
Text Classification (Q)
|
92% |
2586
3.47 KIPS |
|
|
Machine Translation (SP)
|
100% |
1550
26.7 IPS |
|
|
Machine Translation (HP)
|
100% |
1556
26.8 IPS |
|
|
Machine Translation (Q)
|
100% |
1509
26.0 IPS |
